S Oracle Cloud Infrastructure AI Foundations LVC

Course Description

S Oracle Cloud Infrastructure AI Foundations LVC develops practical capability in ai, machine learning, deep learning, and generative ai foundations and oci ai services, language, vision, speech, document understanding, and anomaly detection. The course connects Oracle architecture, configuration, development, or functional processing to ownership, security, data quality, controls, and measurable acceptance criteria.

The later modules cover oci generative ai, models, prompting, embeddings, vector search, and rag and responsible ai, security, evaluation, cost awareness, and adoption planning. Learners use use-case map, service comparison, sample AI outputs, prompt tests to distinguish configuration defects from data, access, integration, performance, or operational failures.

By completing the learning path, participants can support a business team selecting suitable OCI AI services and defining a responsible proof of concept with measurable value. They also produce an improvement plan covering validation, exception handling, rollback, ownership, monitoring, and production support.

What You Will Learn

• Assess readiness for AI, Machine Learning, including ownership and prerequisites.
• Establish Deep Learning, Generative AI Foundations and demonstrate success with use-case map.
• Carry out OCI AI Services, Language with recorded inputs, controls, and outputs.
• Reduce exposure to poor use-case fit by validating Vision, Speech, Document Understanding at the correct stage.
• Develop hands-on capability in OCI Generative AI, Models using representative data.
• Measure Prompting, Embeddings, Vector Search with evaluation criteria and explain any variance.
• Support Responsible AI, Security through diagnostics, recovery planning, and operational documentation.
• Troubleshoot automation bias by reviewing Evaluation, Cost Awareness, Adoption Planning without introducing an unverified production change.

SkillDynamo Training Approach

Delivery combines Oracle-specific demonstrations, guided hands-on exercises, scenario analysis, validation checklists, structured troubleshooting, peer review, and a final improvement plan. Learners document assumptions, settings, data, outputs, exceptions, corrective actions, rollback needs, approvals, evidence, and operational responsibilities.